/*
 *    WaveformGenerator.java
 *    Copyright (C) 2007 University of Waikato, Hamilton, New Zealand
 *    @author Richard Kirkby (rkirkby@cs.waikato.ac.nz)
 *
 *    This program is free software; you can redistribute it and/or modify
 *    it under the terms of the GNU General Public License as published by
 *    the Free Software Foundation; either version 2 of the License, or
 *    (at your option) any later version.
 *
 *    This program is distributed in the hope that it will be useful,
 *    but WITHOUT ANY WARRANTY; without even the implied warranty of
 *    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 *    GNU General Public License for more details.
 *
 *    You should have received a copy of the GNU General Public License
 *    along with this program; if not, write to the Free Software
 *    Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
 */
package moa.streams.generators;

import java.util.Random;

import moa.core.InstancesHeader;
import moa.core.ObjectRepository;
import moa.options.AbstractOptionHandler;
import moa.options.FlagOption;
import moa.options.IntOption;
import moa.streams.InstanceStream;
import moa.tasks.TaskMonitor;
import weka.core.Attribute;
import weka.core.FastVector;
import weka.core.Instance;
import weka.core.Instances;

public class WaveformGenerator extends AbstractOptionHandler implements
		InstanceStream {

	@Override
	public String getPurposeString() {
		return "Generates a problem of predicting one of three waveform types.";
	}
	
	private static final long serialVersionUID = 1L;

	public static final int NUM_CLASSES = 3;

	public static final int NUM_BASE_ATTRIBUTES = 21;

	public static final int TOTAL_ATTRIBUTES_INCLUDING_NOISE = 40;

	protected static final int hFunctions[][] = {
			{ 0, 1, 2, 3, 4, 5, 6, 5, 4, 3, 2, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0 },
			{ 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 3, 4, 5, 6, 5, 4, 3, 2, 1, 0 },
			{ 0, 0, 0, 0, 0, 1, 2, 3, 4, 5, 6, 5, 4, 3, 2, 1, 0, 0, 0, 0, 0 } };

	public IntOption instanceRandomSeedOption = new IntOption(
			"instanceRandomSeed", 'i',
			"Seed for random generation of instances.", 1);

	public FlagOption addNoiseOption = new FlagOption("addNoise", 'n',
			"Adds noise, for a total of 40 attributes.");

	protected InstancesHeader streamHeader;

	protected Random instanceRandom;

	@Override
	protected void prepareForUseImpl(TaskMonitor monitor,
			ObjectRepository repository) {
		// generate header
		FastVector attributes = new FastVector();
		int numAtts = this.addNoiseOption.isSet() ? TOTAL_ATTRIBUTES_INCLUDING_NOISE
				: NUM_BASE_ATTRIBUTES;
		for (int i = 0; i < numAtts; i++) {
			attributes.addElement(new Attribute("att" + (i + 1)));
		}
		FastVector classLabels = new FastVector();
		for (int i = 0; i < NUM_CLASSES; i++) {
			classLabels.addElement("class" + (i + 1));
		}
		attributes.addElement(new Attribute("class", classLabels));
		this.streamHeader = new InstancesHeader(new Instances(
				getCLICreationString(InstanceStream.class), attributes, 0));
		this.streamHeader.setClassIndex(this.streamHeader.numAttributes() - 1);
		restart();
	}

	public long estimatedRemainingInstances() {
		return -1;
	}

	public InstancesHeader getHeader() {
		return this.streamHeader;
	}

	public boolean hasMoreInstances() {
		return true;
	}

	public boolean isRestartable() {
		return true;
	}

	public Instance nextInstance() {
		InstancesHeader header = getHeader();
		Instance inst = new Instance(header.numAttributes());
		inst.setDataset(header);
		int waveform = this.instanceRandom.nextInt(NUM_CLASSES);
		int choiceA = 0, choiceB = 0;
		switch (waveform) {
		case 0:
			choiceA = 0;
			choiceB = 1;
			break;
		case 1:
			choiceA = 0;
			choiceB = 2;
			break;
		case 2:
			choiceA = 1;
			choiceB = 2;
			break;

		}
		double multiplierA = this.instanceRandom.nextDouble();
		double multiplierB = 1.0 - multiplierA;
		for (int i = 0; i < NUM_BASE_ATTRIBUTES; i++) {
			inst.setValue(i, (multiplierA * hFunctions[choiceA][i])
					+ (multiplierB * hFunctions[choiceB][i])
					+ this.instanceRandom.nextGaussian());
		}
		if (this.addNoiseOption.isSet()) {
			for (int i = NUM_BASE_ATTRIBUTES; i < TOTAL_ATTRIBUTES_INCLUDING_NOISE; i++) {
				inst.setValue(i, this.instanceRandom.nextGaussian());
			}
		}
		inst.setClassValue(waveform);
		return inst;
	}

	public void restart() {
		this.instanceRandom = new Random(this.instanceRandomSeedOption
				.getValue());
	}

	public void getDescription(StringBuilder sb, int indent) {
		// TODO Auto-generated method stub

	}

}
